Triple
T23669308
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paulina station |
E584683
|
entity |
| Predicate | hasFarecardSystem |
P149028
|
FINISHED |
| Object | Ventra |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Ventra | Statement: [Paulina station, hasFarecardSystem, Ventra]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFarecardSystem Context triple: [Paulina station, hasFarecardSystem, Ventra]
-
A.
hasFareCardVendor
Indicates that an entity provides or is associated with a machine or service point where fare cards can be purchased, reloaded, or otherwise obtained.
-
B.
fareCardSystem
chosen
Indicates a system that manages the issuance, validation, and payment processing of fare cards for transportation or access services.
-
C.
hasFareZoneSystem
Indicates that an entity uses or is associated with a particular fare zone system for determining travel costs or ticketing.
-
D.
hasAutomaticFareCollection
Indicates that an entity is equipped with a system that automatically collects fares or payments from users without manual processing.
-
E.
fareSystemFeature
Indicates that a fare system possesses or supports a particular feature, function, or characteristic related to how fares are calculated, managed, or used.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69e24901421881908c17a5293bdd4a8e |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b40dc0ec8190b558e30dbebf491f |
completed | April 29, 2026, 7:32 a.m. |
| PD | Predicate disambiguation | batch_69f118dd13008190a8799b4e9cadbd79 |
completed | April 28, 2026, 8:30 p.m. |
Created at: April 17, 2026, 6:50 p.m.